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Pregled bibliografske jedinice broj: 499479

Targeting and synchronization at tokamak with recurrent artificial neural networks


Rastović, Danilo
Targeting and synchronization at tokamak with recurrent artificial neural networks // Neural computing & applications, 21 (2012), 5; 1065-1069 doi:10.1007/s00521-011-0527-4 (međunarodna recenzija, članak, znanstveni)


Naslov
Targeting and synchronization at tokamak with recurrent artificial neural networks

Autori
Rastović, Danilo

Izvornik
Neural computing & applications (0941-0643) 21 (2012), 5; 1065-1069

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Tokamak; synchronization; recurrent artificial neural networks

Sažetak
In this letter, we propose an adaptive recurrent artificial neural networks synchronization of H-mode and Edge Localized Modes that is important for obtaining a long pulse tokamak without disruption regime. The deterministic part of the plasma behavior should be synchronized with stochastic part by introducing stochastic artificial neural network.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo



POVEZANOST RADA


Projekt / tema
120-1201842-3048 - Umjetna inteligencija u upravljanju složenim nelinearnim dinamičkim sustavima (Josip Kasać, )

Ustanove
Fakultet strojarstva i brodogradnje, Zagreb,
Tehničko veleučilište u Zagrebu

Autor s matičnim brojem:
Danilo Rastović, (106700)

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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